At a Glance
- Tasks: Design and deliver cutting-edge AI solutions in a hybrid role.
- Company: Leading technology consultancy with a focus on innovation.
- Benefits: Competitive salary, bonus, and opportunities for professional growth.
- Other info: Join a dynamic team and work on high-impact AI programmes.
- Why this job: Make a real impact in AI while shaping best practices.
- Qualifications: Strong AI engineering background and excellent Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
I’m currently working with a leading technology consultancy that is looking for a Senior Principal AI Engineer to help design, build, and deliver production-grade AI solutions across complex enterprise environments. This is a senior role combining hands‑on AI engineering, technical leadership, architecture, and client‑facing consulting, working across the full AI lifecycle from concept through to deployment and optimisation.
What you’ll be doing:
- Designing and delivering end‑to‑end AI/ML solutions, including Generative AI and classical ML use cases
- Building scalable AI pipelines across data ingestion, feature engineering, training, evaluation, deployment, and monitoring
- Applying MLOps best practices including CI/CD, model versioning, automated retraining, monitoring, and rollback
- Defining AI solution architectures for enterprise‑scale environments
- Evaluating emerging technologies including LLMs, GenAI platforms, and vector databases
- Leading technical workshops and advising clients on AI strategy, feasibility, and implementation
- Driving Responsible AI principles around explainability, governance, privacy, and compliance
- Mentoring AI Engineers and Data Scientists
What we’re looking for:
- Strong background in AI Engineering, ML Engineering, or similar roles delivering production AI systems
- Excellent Python/software engineering capability
- Experience with frameworks such as PyTorch, TensorFlow, or scikit‑learn
- Strong MLOps experience deploying models into live environments
- Cloud experience across Azure, AWS, or GCP
- Ability to communicate technical concepts clearly with stakeholders
Location: London (Hybrid)
Employment: Permanent
This is a great opportunity to work on high‑impact AI programmes while helping shape best practices for enterprise AI delivery.
AI Practice Lead employer: DeepRec.ai
At DeepRec.ai, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Greater London. Our commitment to employee growth is evident through our focus on cutting-edge AI technologies and the opportunity to lead transformative projects that have a real impact on the future of science. With competitive compensation, a supportive environment, and the chance to work alongside industry leaders, we provide a unique platform for engineers passionate about making a difference in the world of AI.
StudySmarter Expert Advice🤫
We think this is how you could land AI Practice Lead
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at DeepRec.ai or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to DeepRec.ai.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like DeepRec.ai.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like DeepRec.ai that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Practice Lead
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at DeepRec.ai.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at DeepRec.ai and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at DeepRec.ai
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If DeepRec.ai uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
